Adding open in colab button

Author: albertodepaola

recipes/llama_api_providers/examples_with_aws/ReAct_Llama_2_Bedrock-WK.ipynb

@@ -7,6 +7,8 @@
     "# Advanced Techniques\n",
     "## 1. ReAct\n",
     "\n",
+    "Open this notebook in <a href=\"https://colab.research.google.com/github/meta-llama/llama-recipes/blob/main/recipes/llama_api_providers/examples_with_aws/ReAct_Llama_2_Bedrock-WK.ipynb\"><img data-canonical-src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\" src=\"https://camo.githubusercontent.com/f5e0d0538a9c2972b5d413e0ace04cecd8efd828d133133933dfffec282a4e1b/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667\"></a>\n",
+    "\n",
     "LLMs abilities for reasoning (e.g. chain-of-thought CoT prompting) and acting have primarily been studied as separate topics. **ReAct** [Shunyu Yao et al. ICLR 2023](https://arxiv.org/pdf/2210.03629.pdf) (Reason and Act) is a method to generate both reasoning traces and task-specific actions in an interleaved manner.\n",
     "\n",
     "In simple words, we define specific patterns for the language model to follow. This allows the model to act (usually through tools) and reason. Hence the model creates a squence of interleaved thoughts and actions. Such systems that act on an enviroment are usually called **agents** (borrowed from reinforcement learning).\n",